The experience of bodily image for patients with left ventricular assist device by Irena Milaniak, Emilia Witkowska, Marta Cebula, Paulina Tomsia, Grzegorz Wasilewski, Izabela Górkiewicz-Kot, Sylwia Wiśniowska-Śmiałek, Michał Kaleta, Karol Wierzbicki, Karol Wierzbicki

“…The presence of anxiety and depressive symptoms and complications after LVAD significantly predicted low body image concerns.DiscussionHealthcare professionals should be aware of challenges regarding body image faced by LVAD-implanted patients and address related factors, especially anxiety and depression.…”
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A study protocol for individualized prognostic counselling in the palliative phase by Boyd Noël van den Besselaar, A. Sewnaik, M. C. Dorr, A. Hoesseini, J. A. Hardillo, R. J. Baatenburg de Jong, M.P.J. Offerman

“…Patients in this stage often have increased prognostic information needs. Unfortunately, predicting individual life expectancy in this phase is particularly challenging, as physicians and patients tend to overestimate survival. …”
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Inhibitory effects of limonin on the proliferation of non-small cell lung cancer cells via targeting S-phase kinase-associated protein 2 by Zhu Jiaxian, Zhang Mengting, Li Shengqing, Liu Yongqiang

“…Cell thermal shift assay (CETSA) was used to demonstrate the binding capability of limonin with target proteins, and molecular docking was employed to predict the interaction sites between limonin and target proteins. …”
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Measurable residual disease as predictor of post–day +100 relapses after allografting in adult AML by Naveed Ali, Megan Othus, Eduardo Rodríguez-Arbolí, Corentin Orvain, Filippo Milano, Brenda M. Sandmaier, Chris Davis, Ryan S. Basom, Frederick R. Appelbaum, Roland B. Walter

“…To examine the role of MFC MRD testing to predict later relapses, we examined 935 adults with AML or myelodysplastic neoplasm/AML transplanted in first or second morphologic remission who underwent bone marrow restaging studies between day 70 and 100 after HCT and were alive and without relapse by day +100. …”
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Simultaneous Multiband Photometry of the Early Optical Afterglow of GRB 240825A with Mephisto by Yehao Cheng, Yu Pan, Yuan-Pei Yang, Jinghua Zhang, Guowang Du, Yuan Fang, Brajesh Kumar, Helong Guo, Xinzhong Er, Xinlei Chen, Chenxu Liu, Tao Wang, Zhenfei Qin, Yicheng Jin, Xingzhu Zou, Xuhui Han, Pinpin Zhang, Liping Xin, Chao Wu, Jianhui Lian, Xiangkun Liu, Xiaowei Liu

“…To reconcile the measured much softer spectral energy distribution (SED) with that predicted by the standard afterglow model, an extra host-galaxy extinction of E _B _− _V  ∼ (0.37–0.57) mag is required. …”
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Impact of sperm DNA fragmentation index on assisted reproductive outcomes: a retrospective analysis by Bin Yang, Leizhen Xia, Rufei Deng, Liping Wu, Zhiqin Zhang, Xingwu Wu, Tao Ding, Yan Zhao, Jialyu Huang, Jialyu Huang, Zhihui Huang

“…The role of DFI as a predictive factor in assisted reproduction, especially regarding offspring outcomes, requires further investigation with larger sample sizes.…”
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Comparative survival outcomes of neoadjuvant and adjuvant therapy in patients with T1c, node-negative, triple-negative breast cancer: A population-based analysis by Yi-Zi Zheng, Jia-Qi Ying, Ting-Ting Wu, Yong-Hui Su, Ou-Chen Wang

“…Logistic regression models were utilized to identify predictive factors for response to NAT. Results: A total of 1033 patient pairs passed the PSM process, resulting in a well-balanced distribution. …”
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Comparative Evaluation and Measure of Accuracy of ELISAs, CLIAs, and ECLIAs for the Detection of HIV Infection among Blood Donors in China by Le Chang, Junpeng Zhao, Fei Guo, Huimin Ji, Lu Zhang, Xinyi Jiang, Lunan Wang

“…CLIA and ECLIA assay had similar sensitivities with ELISAs but showed higher specificity (CLIA: 99.1%, 885/893; ECLIA: 99.0%, 884/893), concordance rate (CLIA: 99.2%, 1021/1029; ECLIA: 99.1%, 1020/1029), and positive predictive value (PPV) (CLIA: 94.4%, 136/144; ECLIA: 93.8%, 136/145) than most of ELISA kits (>5 ELISAs) (P<0.05). …”
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Monitoring changes of forest height in California by Samuel Favrichon, Jake Lee, Yan Yang, Yan Yang, Ricardo Dalagnol, Ricardo Dalagnol, Fabien Wagner, Le Bienfaiteur Sagang, Le Bienfaiteur Sagang, Sassan Saatchi, Sassan Saatchi, Sassan Saatchi

“…We train a deep neural network to predict forest height metrics at 10-m resolution from radar and optical satellite imagery. …”
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Identifying pesticide mixtures at country-wide scale by Cairo, Milena, Monnet, Anne-Christine, Robin, Stéphane, Porcher, Emmanuelle, Fontaine, Colin

“…The consequences of such exposure are still poorly understood, first because of potentially strong synergistic effects, making cocktails effects not predictable from the effects of single compounds, but also because little is known about the actual exposure of organisms to pesticide mixtures in nature. …”
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Combination of Hotspot Mutations With Methylation and Fragmentomic Profiles to Enhance Multi‐Cancer Early Detection by Thi Hue Hanh Nguyen, Giang Hoang Vu, Tu Thi Nguyen, Tuan Anh Nguyen, Vu Uyen Tran, Luyen Thi Vu, Giang Thi Huong Nguyen, Nhat Duy Nguyen, Trung Hieu Tran, Van Thien Chi Nguyen, Thanh Dat Nguyen, Trong Hieu Nguyen, Dac Ho Vo, Thi Tuong Vi Van, Thanh Thi Do, Minh Phong Le, Le Anh Khoa Huynh, Duy Sinh Nguyen, Hung Sang Tang, Hoai‐Nghia Nguyen, Minh‐Duy Phan, Hoa Giang, Lan N. Tu, Le Son Tran

“…The combination of hotspot mutations with SPOT‐MAS predictions improved early‐stage cancer detection, achieving an overall sensitivity of 78.5% at a specificity of 97.7%. …”
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Therapeutic target genes and regulatory networks of gallic acid in cervical cancer by Zhixi You, Ye Lei, Yongkang Yang, Zhihui Zhou, Xu Chao, Keyi Ju, Songyi Wang, Yuanyuan Li, Yuanyuan Li

“…Furthermore, the upstream microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) of the candidate genes were predicted using the online tools of MirDIP, TarBase, and ENCORI. …”
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Iterative optimization annotation pipeline and ALSS-YOLO-Seg for efficient banana plantation segmentation in UAV imagery by Ang He, Ang He, Ximei Wu, Ximei Wu, Xing Xu, Xing Xu, Jing Chen, Jing Chen, Xiaobin Guo, Xiaobin Guo, Sheng Xu, Sheng Xu

“…By identifying and classifying planted areas, crop areas can be calculated, which is indispensable for accurate yield predictions. However, segmenting banana plantation scenes requires a substantial amount of annotated data, and manual labeling of these images is both timeconsuming and labor-intensive, limiting the development of large-scale datasets. …”
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Non-Linear Biomechanical Evaluation and Comparison in the Assessment of Three Different Piece Dental Implant Systems for the Molar Region: A Finite Element Study by Jesus Alejandro Serrato-Pedrosa, Ignacio Villanueva-Fierro, Rodrigo Arturo Marquet-Rivera, Rosa Alicia Hernández-Vázquez, Salvador Cruz-Lopez, Verónica Loera-Castañeda

“…This biomechanical approach could provide a promising strategy for predicting micro-strains and micromotion in implant system pieces and geometries. …”
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Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe by C. Poppe Terán, C. Poppe Terán, C. Poppe Terán, B. S. Naz, B. S. Naz, H. Vereecken, H. Vereecken, R. Baatz, R. A. Fisher, H.-J. Hendricks Franssen, H.-J. Hendricks Franssen

“…</p> <p>Here, we evaluated CLM5's predictions of water and energy fluxes using observations from eddy covariance stations from the Integrated Carbon Observation System (ICOS), remote sensing, and reanalysis data sets. …”
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Organizational readiness for change towards implementing a sepsis survivor hospital to home transition-in-care protocol by Elaine Sang, Elaine Sang, Ryan Quinn, Michael A. Stawnychy, Michael A. Stawnychy, Michael A. Stawnychy, Michael A. Stawnychy, Jiyoun Song, Jiyoun Song, Jiyoun Song, Karen B. Hirschman, Karen B. Hirschman, Karen B. Hirschman, Sang Bin You, Sang Bin You, Katherine S. Pitcher, Katherine S. Pitcher, Nancy A. Hodgson, Nancy A. Hodgson, Nancy A. Hodgson, Patrik Garren, Melissa O'Connor, Sungho Oh, Sungho Oh, Kathryn H. Bowles, Kathryn H. Bowles, Kathryn H. Bowles, Kathryn H. Bowles

“…Additional studies may assess the predictive validity of ORIC towards implementation success.…”
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Prognostic value of HSP27 in 28-day mortality in septic ICU patients: a retrospective cohort study by Lihua Yao, Lihua Yao, Zaiwei Fan, Fangyi Yao, Xiaozhong Wang

“…Receiver operating characteristic (ROC) curve analysis revealed an area under the curve (AUC) of 0.720 (95% CI: 0.605–0.817, p &lt; 0.001) for HSP27 in predicting sepsis prognosis. Survival analysis demonstrated that patients with high serum HSP27 levels (≥2.61 ng/mL) had a worse prognosis than those with low levels (&lt;2.61 ng/mL).ConclusionHSP27 shows potential as a biomarker for the diagnosis and prognosis of sepsis, however, further research is necessary to solidify its clinical utility.…”
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Predictors of chronic pain and level of physical function in total knee arthroplasty: a protocol for a systematic review and meta-analysis by Jens Ivar Brox, Christopher James Rose, Anners Lerdal, Øystein Skare, Unni Olsen, Maren Falch Lindberg, Eva Marie-Louise Denison, Caryl Lynn Gay, Arild Aamodt, Ove Furnes, Kathryn A Lee

“…Estimates of association between each outcome and any preoperative or intraoperative factor that may predict chronic pain or impaired physical function will be extracted from the included studies, where possible. …”
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Constraints on triggered seismicity and its control on permeability evolution by Derek Elsworth, Ziyan Li, Pengliang Yu, Mengke An, Fengshou Zhang, Rui Huang, Zihan Sun, Guanglei Cui, Tianyu Chen, Quan Gan, Yixin Zhao, Jishan Liu, Shimin Liu

“…Machine learning deciphers the principal features of MEQs and the resulting permeability evolution that best track permeability changes – with transfer learning methods allowing robust predictions across multiple eological settings. Changes in permeability at reactivated fractures in both shear and extensional modes suggest that permeability change (Δk) scales with the seismic moment (M) of individual MEQs as Δk∝M. …”
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Predictors and Outcomes of Hematoma Expansion and Neurological Decline in Intracerebral Hemorrhage: A Multisite Mobile Stroke Unit Study by Asish K. Gulati, Tianwen Ma, Isaiah Rolle, Ryan Peterson, Bianca Pirlog, Justine Chen, Megan Heckathorn, Jonathan Ratcliff, Nicolas Bianchi, Carol Fleming, Michael Frankel, James Grotta, Ritvij Bowry, Stephanie Parker, William Hicks, Digvijaya Navalkele

“…The interrater reliability for radiographic signs of HE was also assessed. Predictive factors were analyzed using multiple logistic regression models. …”
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